This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Homing endonucleases are DNA-cleaving enzymes that generate double strand breaks at specific genomic invasion sites. These proteins are attractive for many biotech and medical applications, including gene therapy, because they have the potential to activate site-specific recombination events that result in the insertion, deletion, mutation or correction of DNA sequences. In this project, we develop computational methods to identify regions in human DNA that are bound and cleaved by homing endonucleases with extremely high accuracy. Specifically, we developed a neural network classifier that can discriminate with high accuracy between sites that are bound by the enzyme and sites that are both bound and cleaved. In this context, higher order feature representations have the potential to capture the statistical patterns that contribute to the cleavage process.